M.SC. in Computer Engineering (Without Thesis)

EEE 504 | Course Introduction and Application Information

Course Name

Bankaları / Wavelets and Filter Banks

Code	Semester	Theory (hour/week)	Application/Lab (hour/week)	Local Credits	ECTS
EEE 504	Fall/Spring	3	0	3	7.5

Prerequisites	None
Course Language	English
Course Type	Elective
Course Level	Second Cycle
Mode of Delivery	-
Teaching Methods and Techniques of the Course	-
National Occupation Classification	-
Course Coordinator	-
Course Lecturer(s)	Doç. Dr. Levent EREN
Assistant(s)	-

Course Objectives

The objective of this course is to establish the theory necessary to understand and use wavelets and related constructions. A particular emphasis will be put on constructions that are amenable to efficient algorithms.

Learning Outcomes

#	Content	PC Sub	* Contribution Level
#	Content	PC Sub	1	2	3	4	5
1	learn to use and discuss the basic techniques/algorithms of the field,
2	have knowledge of the advantages and limitations of different wavelet decomposition algorithms,
3	be able to evaluate potential applications of wavelet decomposition techniques,
4	be able to design and implement wavelet decomposition algorithms using Matlab and signal processing toolbox.

Course Description

The course will consist of lectures, homework assignments and a project on a topic related to the student's area of interest. We will aim for the right balance of theory and applications. Analysis of Filter Banks and Wavelets, Design Methods, Applications, Hands-on Experience with Software.

Course Category	Core Courses
	Major Area Courses
	Supportive Courses
	Media and Management Skills Courses
	Transferable Skill Courses

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week	Subjects	Related Preparation	Learning Outcome
1	Why wavelets, filter banks, and multiresolution analysis, Signal spaces and operators ,Review of Fourier theory	Fourier and Wavelet Signal Processing, Kovacevic, Goyal and Vetterli, Ch. 1
2	Multirate signal processing, Time-frequency analysis	Fourier and Wavelet Signal Processing, Kovacevic, Goyal and Vetterli, Ch. 1
3	Series expansions of discrete-time signals, Analysis and design of filter banks	Fourier and Wavelet Signal Processing, Kovacevic, Goyal and Vetterli, Ch. 1
4	Orthogonal and biorthogonal filter banks, Tree-structured filter banks, Discrete wavelet transform	Fourier and Wavelet Signal Processing, Kovacevic, Goyal and Vetterli, Ch. 3
5	Multiresolution analysis, Iterated filter banks, Wavelets and filter banks	Fourier and Wavelet Signal Processing, Kovacevic, Goyal and Vetterli, Ch. 6
6	Wavelet series and its properties, Regularity and approximation properties	Fourier and Wavelet Signal Processing, Kovacevic, Goyal and Vetterli, Ch. 3
7	Frame theory, Oversampled filter banks	Fourier and Wavelet Signal Processing, Kovacevic, Goyal and Vetterli, Ch. 4
8	Continuous wavelet and short-time Fourier transforms	Fourier and Wavelet Signal Processing, Kovacevic, Goyal and Vetterli, Ch. 4
9	Midterm
10	Sparse representation, Linear and non-linear approximation in various bases	Fourier and Wavelet Signal Processing, Kovacevic, Goyal and Vetterli, Ch. 5
11	Non-linear signal estimation, Multidimensional filter banks and wavelets	Fourier and Wavelet Signal Processing, Kovacevic, Goyal and Vetterli, Ch. 5
12	Multiscale geometric representation and processing, Compressed sensing	Fourier and Wavelet Signal Processing, Kovacevic, Goyal and Vetterli, Ch. 7
13	Speech, audio, image, and video compression, Signal denoising	Fourier and Wavelet Signal Processing, Kovacevic, Goyal and Vetterli, Ch. 7
14	Feature extraction, Inverse problems	Fourier and Wavelet Signal Processing, Kovacevic, Goyal and Vetterli, Ch. 7
15	Review of the Semester
16	Review of the Semester

Course Notes/Textbooks	The textbook referenced above and course slides
Suggested Readings/Materials	Related Research Papers

EVALUATION SYSTEM

Semester Activities	Number	Weighting	LO 1	LO 2	LO 3	LO 4
Participation
Laboratory / Application
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments	4	20
Presentation / Jury
Project	1	40
Seminar / Workshop
Oral Exams
Midterm	1	40
Final Exam
Total

Weighting of Semester Activities on the Final Grade		100
Weighting of End-of-Semester Activities on the Final Grade
Total

ECTS / WORKLOAD TABLE

Semester Activities	Number	Duration (Hours)	Workload
Theoretical Course Hours (Including exam week: 16 x total hours)	16	3	48
Laboratory / Application Hours (Including exam week: '.16.' x total hours)	16		0
Study Hours Out of Class	15	4	60
Field Work			0
Quizzes / Studio Critiques			0
Portfolio			0
Homework / Assignments	4	15	60
Presentation / Jury			0
Project	1	37	37
Seminar / Workshop			0
Oral Exam			0
Midterms	1	20	20
Final Exam			0
		Total	225

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

#	PC Sub	Program Competencies/Outcomes	* Contribution Level
#	PC Sub	Program Competencies/Outcomes	1	2	3	4	5
1	Accesses information in breadth and depth by conducting scientific research in Computer Engineering, evaluates, interprets and applies information.		-	-	-	X	-
2	Is well-informed about contemporary techniques and methods used in Computer Engineering and their limitations.		-	-	X	-	-
3	Uses scientific methods to complete and apply information from uncertain, limited or incomplete data, can combine and use information from different disciplines.		-	-	-	X	-
4	Is informed about new and upcoming applications in the field and learns them whenever necessary.		-	-	-	-	X
5	Defines and formulates problems related to Computer Engineering, develops methods to solve them and uses progressive methods in solutions.		-	-	-	-	X
6	Develops novel and/or original methods, designs complex systems or processes and develops progressive/alternative solutions in designs.		-	-	-	X	-
7	Designs and implements studies based on theory, experiments and modelling, analyses and resolves the complex problems that arise in this process.		-	-	-	X	-
8	Can work effectively in interdisciplinary teams as well as teams of the same discipline, can lead such teams and can develop approaches for resolving complex situations, can work independently and takes responsibility.		-	-	X	-	-
9	Engages in written and oral communication at least in Level B2 of the European Language Portfolio Global Scale.		-	-	X	-	-
10	Communicates the process and the results of his/her studies in national and international venues systematically, clearly and in written or oral form.		-	-	X	-	-
11	Is knowledgeable about the social, environmental, health, security and law implications of Computer Engineering applications, knows their project management and business applications, and is aware of their limitations in Computer Engineering applications.		-	-	X	-	-
12	Highly regards scientific and ethical values in data collection, interpretation, communication and in every professional activity.		-	X	-	-	-